In driver assistance systems, for example in collision warning systems, a radar sensor is frequently used for locating objects in the surroundings, in particular ahead of the host vehicle, the sensor, for example, being capable of measuring distances and relative speeds of the located objects according to the FMCW (frequency-modulated continuous wave) principle. Preceding vehicles which have an absolute speed which is comparable to the speed of the host vehicle and therefore do not constitute a relevant obstacle are identifiable in that the relative speed measured by the radar sensor is significantly smaller than the speed of the host vehicle in terms of absolute value. If, on the other hand, the measured relative speed of an object is negative (approach) and is equal to the speed of the host vehicle in terms of absolute value, the object is then a stationary object which constitutes a potential obstacle. Based on a certain angle resolution capability, the radar sensor is also capable of determining whether the object is situated on the roadway or on the edge of the roadway. However, even if a stationary object has been located on the roadway, it does not necessarily constitute a real obstacle. For example, even relatively small objects such as cans lying on the roadway or manhole covers set into the pavement cause a radar echo which is difficult to distinguish from the radar echo of a more extensive object constituting a real obstacle.
Nevertheless, in order to make it possible to distinguish between real obstacles and apparent obstacles, one or multiple evaluation functions are used in known driver assistance systems, whose arguments are formed by measured variables which typically have values for real obstacles which are different from those for apparent obstacles.
One example of such a measured variable is, for example, the signal strength of a single located object. The underlying thought is that an extensive object which is more likely to be evaluated as a real obstacle will generally generate a stronger radar echo than an object which is limited in size, such as a small object lying on the roadway, which can be driven over without a problem. Depending on the signal strength of the object, the evaluation function may then assume either the value 1, which means that the object is considered to be a real obstacle, or the value 0, which means that the object is evaluated as an apparent obstacle. However, according to the specific embodiment, the evaluation function may also assume intermediate values between 0 and 1, which indicate varying probabilities that the object is a real obstacle. Ultimately, in order to come to an unambiguous decision, multiple evaluation functions which are based on different criteria are generally linked.
Other examples of measured variables which provide information about the relevance of an object as an obstacle are the elevation angle at which the object is viewed by the radar sensor and changes of this elevation angle over time. A real obstacle will generally be situated at least at the same height as the radar sensor, so that the elevation angle is zero or positive, while a small object lying on the road will generally have a negative elevation angle, which in addition grows more negative with increasing proximity to the object. On the other hand, in the case of a relatively extensive real obstacle, it will frequently happen that the radar echo is received from various elevation angles due to multipath scattering over the road surface. In addition, pitching and steering movements of the host vehicle result in the signal being received from various reflection targets which also have various elevation angles. A sharply fluctuating elevation angle therefore tends to indicate a real obstacle.
Even if multiple criteria, i.e., multiple evaluation functions, are combined, it will not be possible in practice to correctly evaluate all objects which appear. The evaluation functions must therefore be defined in such a way that a reasonable compromise is found between a high hit rate, i.e., a high proportion of real obstacles which are also actually identified as obstacles, and a low false alarm rate, i.e., which may be a low proportion of apparent objects incorrectly evaluated as real obstacles. For this purpose, parameters which determine the characteristics of the evaluation function must be suitably chosen. In the simplest case, the evaluation function is a threshold value function which jumps from 0 to 1 if a certain threshold value is exceeded. In this case, the threshold value constitutes a parameter which must be suitably chosen. In more complex evaluation functions, the parameters may be sets of multiple threshold values or polynomial coefficients or the like.
When establishing these parameters, the avoidance of false alarms will generally have the highest priority, since frequent false alarms may significantly reduce the acceptance of the system and may even constitute a potential hazard in driver assistance systems which actively intervene into the braking system of the vehicle when there is an acute risk of collision. If, however, in order to avoid such false alarms, the parameters are chosen too “conservatively,” a larger proportion of real obstacles will then unavoidably not be identified, thus reducing the usefulness of the system.